グラフ描画
- max_draqdown（リーマンショックの経験から50％とする）
- under2σ（日次リターン過去1年分の）
- over2σ（日次リターン過去1年分の）
2510
tarTicker <- c("2510")
data1 <- daily1 %>%
filter(ticker == tarTicker) %>%
tail(., 300) %>%
mutate(return = close / dplyr::lag(close) - 1)
max_drawdown <- tail(data1$close, 1) * 0.5
under2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.02275)))
over2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.97725)))
tail(data)
174 }
175 rm(tmp_env)
176 }
177 }
178 invisible(names)
179 }
g <- ggplot(NULL) +
geom_line(data = data1, aes(x = date, y = close, colour = ticker)) +
geom_point(data = subset(zandaka, ticker == tarTicker), aes(x = date, y = tanka, colour = ticker)) +
geom_hline(yintercept = max_drawdown, linetype = "dashed", colour = "blue") +
annotate("text", label = "max_drawdown", x = min(data1$date), y = max_drawdown + 10,
colour = "blue") +
geom_hline(yintercept = under2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "-2σ", x = min(data1$date), y = under2sigma - 20,
colour = "blue") +
geom_hline(yintercept = over2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "+2σ", x = min(data1$date), y = over2sigma + 20,
colour = "blue") +
annotate("text", label = round(tail(data1$close, 1) / zandaka[zandaka$ticker == tarTicker, 2] - 1,
digits = 3),
x = max(data1$date) + 5, y = tail(data1$close, 1) + 30, colour = "blue")
ggplotly(g)
2559
tarTicker <- c("2559")
data1 <- daily1 %>%
filter(ticker == tarTicker) %>%
tail(., 300) %>%
mutate(return = close / dplyr::lag(close) - 1)
max_drawdown <- tail(data1$close, 1) * 0.5
under2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.02275)))
over2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.97725)))
tail(data)
174 }
175 rm(tmp_env)
176 }
177 }
178 invisible(names)
179 }
g <- ggplot(NULL) +
geom_line(data = data1, aes(x = date, y = close, colour = ticker)) +
geom_point(data = subset(zandaka, ticker == tarTicker), aes(x = date, y = tanka, colour = ticker)) +
geom_hline(yintercept = max_drawdown, linetype = "dashed", colour = "blue") +
annotate("text", label = "max_drawdown", x = min(data1$date), y = max_drawdown + 10,
colour = "blue") +
geom_hline(yintercept = under2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "-2σ", x = min(data1$date), y = under2sigma - 20,
colour = "blue") +
geom_hline(yintercept = over2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "+2σ", x = min(data1$date), y = over2sigma + 20,
colour = "blue") +
annotate("text", label = round(tail(data1$close, 1) / zandaka[zandaka$ticker == tarTicker, 2] - 1,
digits = 3),
x = max(data1$date) + 5, y = tail(data1$close, 1) + 30, colour = "blue")
ggplotly(g)
TMF
tarTicker <- c("TMF")
data1 <- daily1 %>%
filter(ticker == tarTicker) %>%
tail(., 300) %>%
mutate(return = close / dplyr::lag(close) - 1)
max_drawdown <- tail(data1$close, 1) * 0.5
under2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.02275)))
over2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.97725)))
tail(data)
174 }
175 rm(tmp_env)
176 }
177 }
178 invisible(names)
179 }
g <- ggplot(NULL) +
geom_line(data = data1, aes(x = date, y = close, colour = ticker)) +
geom_point(data = subset(zandaka, ticker == tarTicker), aes(x = date, y = tanka, colour = ticker)) +
geom_hline(yintercept = max_drawdown, linetype = "dashed", colour = "blue") +
annotate("text", label = "max_drawdown", x = min(data1$date), y = max_drawdown + 10,
colour = "blue") +
geom_hline(yintercept = under2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "-2σ", x = min(data1$date), y = under2sigma - 20,
colour = "blue") +
geom_hline(yintercept = over2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "+2σ", x = min(data1$date), y = over2sigma + 20,
colour = "blue") +
annotate("text", label = round(tail(data1$close, 1) / zandaka[zandaka$ticker == tarTicker, 2] - 1,
digits = 3),
x = max(data1$date) + 5, y = tail(data1$close, 1) + 30, colour = "blue")
ggplotly(g)
bitcoin
tarTicker <- c("bitcoin")
data1 <- daily1 %>%
filter(ticker == tarTicker) %>%
tail(., 300) %>%
mutate(return = close / dplyr::lag(close) - 1)
max_drawdown <- tail(data1$close, 1) * 0.5
under2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.02275)))
over2sigma <- tail(data1$close, 1) * (1 + quantile( na.omit(data1$return), c(0.97725)))
tail(data)
174 }
175 rm(tmp_env)
176 }
177 }
178 invisible(names)
179 }
g <- ggplot(NULL) +
geom_line(data = data1, aes(x = date, y = close, colour = ticker)) +
geom_point(data = subset(zandaka, ticker == tarTicker), aes(x = date, y = tanka, colour = ticker)) +
geom_hline(yintercept = max_drawdown, linetype = "dashed", colour = "blue") +
annotate("text", label = "max_drawdown", x = min(data1$date), y = max_drawdown + 10,
colour = "blue") +
geom_hline(yintercept = under2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "-2σ", x = min(data1$date), y = under2sigma - 20,
colour = "blue") +
geom_hline(yintercept = over2sigma, linetype = "dashed", colour = "blue") +
annotate("text", label = "+2σ", x = min(data1$date), y = over2sigma + 20,
colour = "blue") +
annotate("text", label = round(tail(data1$close, 1) / zandaka[zandaka$ticker == tarTicker, 2] - 1,
digits = 3),
x = max(data1$date) + 5, y = tail(data1$close, 1) + 30, colour = "blue")
ggplotly(g)